code: def _xywh2cs(x, y, w, h, aspect_ratio, pixel_std=200):
      center = np.zeros((2), dtype=np.float32)
      center[0] = x + w * 0.5
      center[1] = y + h * 0.5
      if w > aspect_ratio * h:
          h = w * 1.0 / aspect_ratio
      elif w < aspect_ratio * h:
          w = h * aspect_ratio
      scale = np.array(
          [w * 1.0 / pixel_std, h * 1.0 / pixel_std], dtype=np.float32
      )
      return center, scale
  
file_path: PaddleHub/modules/image/semantic_segmentation/ace2p/data_feed.py
imports: import os
  import time
  from collections import OrderedDict
  import cv2
  import numpy
  from .processor import get_affine_transform
label_desc: Use image node_id 2 for calling a global function with example usage: _xywh2cs(x, y, w, h, aspect_ratio, pixel_std) and returns: center,  scale